Klinefelter syndrome (KS) is the most common sex-chromosome aneuploidy in humans. Most affected individuals carry one extra X-chromosome (47,XXY karyotype) and the condition presents with a heterogeneous mix of reproductive, physical and psychiatric phenotypes. Although the mechanism(s) by which the supernumerary X-chromosome determines these features of KS are poorly understood, skewed X-chromosome inactivation (XCI), gene-dosage dysregulation, and the parental origin of the extra X-chromosome have all been implicated, suggesting an important role for epigenetic processes. We assessed genomic, methylomic and transcriptomic variation in matched prefrontal cortex and cerebellum samples identifying an individual with a 47,XXY karyotype who was comorbid for schizophrenia and had a notably reduced cerebellum mass compared with other individuals in the study (n = 49). We examined methylomic and transcriptomic differences in this individual relative to female and male samples with 46,XX or 46,XY karyotypes, respectively, and identified numerous locus-specific differences in DNA methylation and gene expression, with many differences being autosomal and tissue-specific. Furthermore, global DNA methylation, assessed via the interrogation of LINE-1 and Alu repetitive elements, was significantly altered in the 47,XXY patient in a tissue-specific manner with extreme hypomethylation detected in the prefrontal cortex and extreme hypermethylation in the cerebellum. This study provides the first detailed molecular characterization of the prefrontal cortex and cerebellum from an individual with a 47,XXY karyotype, identifying widespread tissue-specific epigenomic and transcriptomic alterations in the brain.

The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model.

Results

We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons.

Conclusions

The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing.

For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.

Electronic supplementary material

The online version of this article (doi:10.1186/1756-8935-8-6) contains supplementary material, which is available to authorized users.

Schizophrenia is a severe neuropsychiatric disorder that is hypothesized to result from disturbances in early brain development. There is mounting evidence to support a role for developmentally regulated epigenetic variation in the molecular etiology of the disorder. Here, we describe a systematic study of schizophrenia-associated methylomic variation in the adult brain and its relationship to changes in DNA methylation across human fetal brain development.

Results

We profile methylomic variation in matched prefrontal cortex and cerebellum brain tissue from schizophrenia patients and controls, identifying disease-associated differential DNA methylation at multiple loci, particularly in the prefrontal cortex, and confirming these differences in an independent set of adult brain samples. Our data reveal discrete modules of co-methylated loci associated with schizophrenia that are enriched for genes involved in neurodevelopmental processes and include loci implicated by genetic studies of the disorder. Methylomic data from human fetal cortex samples, spanning 23 to 184 days post-conception, indicates that schizophrenia-associated differentially methylated positions are significantly enriched for loci at which DNA methylation is dynamically altered during human fetal brain development.

Conclusions

Our data support the hypothesis that schizophrenia has an important early neurodevelopmental component, and suggest that epigenetic mechanisms may mediate these effects.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0483-2) contains supplementary material, which is available to authorized users.

Increased understanding about the functional complexity of the genome has led to growing recognition about the role of epigenetic variation in the etiology of schizophrenia. Epigenetic processes act to dynamically control gene expression independently of DNA sequence variation and are known to regulate key neurobiological and cognitive processes in the brain. To date, our knowledge about the role of epigenetic processes in schizophrenia is limited and based on analyses of small numbers of samples obtained from a range of different cell and tissue types. Moving forward, it will be important to establish cause and effect in epigenetic studies of schizophrenia and broaden our horizons beyond DNA methylation. Rather than investigating genetic and epigenetic factors independently, an integrative etiological research paradigm based on the combination of genomic, transcriptomic, and epigenomic analyses is required.

As the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets.

Results

The standard index of DNA methylation at any specific CpG site is β = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas (βs) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive.

Conclusions

Careful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data.

IGF2 is a paternally expressed imprinted gene with an important role in development and brain function. Allele-specific expression of IGF2 is regulated by DNA methylation at three differentially methylated regions (DMRs) spanning the IGF2/H19 domain on human 11p15.5. We have comprehensively assessed DNA methylation and genotype across the three DMRs and the H19 promoter using tissue from a unique collection of well-characterized and neuropathologically-dissected post-mortem human cerebellum samples (n = 106) and frontal cortex samples (n = 51). We show that DNA methylation, particularly in the vicinity of a key CTCF-binding site (CTCF3) in the imprinting control region (ICR) upstream of H19, is strongly correlated with cerebellum weight. DNA methylation at CTCF3 uniquely explains ∼25% of the variance in cerebellum weight. In addition, we report that genetic variation in this ICR is strongly associated with cerebellum weight in a parental-origin specific manner, with maternally-inherited alleles associated with a 16% increase in cerebellum weight compared with paternally-inherited alleles. Given the link between structural brain abnormalities and neuropsychiatric disease, an understanding of the epigenetic and parent-of-origin specific genetic factors associated with brain morphology provides important clues about the etiology of disorders such as schizophrenia and autism.

The ribosome is an evolutionarily conserved organelle essential for cellular function. Ribosome construction requires assembly of approximately 80 different ribosomal proteins (RPs) and four different species of rRNA. As RPs co-assemble into one multi-subunit complex, mutation of the genes that encode RPs might be expected to give rise to phenocopies, in which the same phenotype is associated with loss-of-function of each individual gene. However, a more complex picture is emerging in which, in addition to a group of shared phenotypes, diverse RP gene-specific phenotypes are observed. Here we report the first two mouse mutations (Rps7Mtu and Rps7Zma) of ribosomal protein S7 (Rps7), a gene that has been implicated in Diamond-Blackfan anemia. Rps7 disruption results in decreased body size, abnormal skeletal morphology, mid-ventral white spotting, and eye malformations. These phenotypes are reported in other murine RP mutants and, as demonstrated for some other RP mutations, are ameliorated by Trp53 deficiency. Interestingly, Rps7 mutants have additional overt malformations of the developing central nervous system and deficits in working memory, phenotypes that are not reported in murine or human RP gene mutants. Conversely, Rps7 mouse mutants show no anemia or hyperpigmentation, phenotypes associated with mutation of human RPS7 and other murine RPs, respectively. We provide two novel RP mouse models and expand the repertoire of potential phenotypes that should be examined in RP mutants to further explore the concept of RP gene-specific phenotypes.

Author Summary

Ribosomes are composed of two subunits that each consist of a large number of proteins, and their function of translating mRNA into protein is essential for cell viability. Naturally occurring or genetically engineered mutations within an individual ribosomal protein provide a valuable resource, since the resulting abnormal phenotypes reveal the function of each ribosomal protein. A number of mutations recently identified in mammalian ribosomal subunit genes have confirmed that homozygous loss of function consistently results in lethality; however, haploinsufficiency causes a variety of tissue-specific phenotypes. In this paper, we describe the first mutant alleles of the gene encoding ribosomal protein S7 (Rps7) in mouse. Rps7 haploinsufficiency causes decreased size, abnormal skeletal morphology, mid-ventral white spotting, and eye malformations, phenotypes that also occur with haploinsufficiency for other ribosomal subunits. Additionally, significant apoptosis occurs within the developing central nervous system (CNS) along with subtle behavioral phenotypes, suggesting RPS7 is required for CNS development. Mutation of human RPS7 has been implicated in Diamond-Blackfan anemia (DBA), yet the murine alleles do not present an analogous phenotype. The phenotypes we observe in the Rps7 mouse mutants indicate RPS7 should be considered as a candidate for a broader spectrum of human diseases.

Insulin-like growth factor 2 (Igf2) is a paternally expressed imprinted gene regulating fetal growth, playing an integral role in the development of many tissues including the brain. The parent-of-origin specific expression of Igf2 is largely controlled by allele-specific DNA methylation at CTCF-binding sites in the imprinting control region (ICR), located immediately upstream of the neighboring H19 gene. Previously we reported evidence of a negative correlation between DNA methylation in this region and cerebellum weight in humans.

Results

We quantified cerebellar DNA methylation across all four CTCF binding sites spanning the murine Igf2/H19 ICR in an outbred population of Heterogeneous Stock (HS) mice (n = 48). We observe that DNA methylation at the second and third CTCF binding sites in the Igf2/H19 ICR shows a negative relationship with cerebellar mass, reflecting the association observed in human post-mortem cerebellum tissue.

Conclusions

Given the important role of the cerebellum in motor control and cognition, and the link between structural cerebellar abnormalities and neuropsychiatric phenotypes, the identification of epigenetic factors associated with cerebellum growth and development may provide important insights about the etiology of psychiatric disorders.

Cyclin-dependent kinase 5 is activated by small subunits, of which p35 is the most abundant. The functions of cyclin-dependent kinase 5 signalling in cognition and cognitive disorders remains unclear. Here, we show that in schizophrenia, a disorder associated with impaired cognition, p35 expression is reduced in relevant brain regions. Additionally, the expression of septin 7 and OPA1, proteins downstream of truncated p35, is decreased in schizophrenia. Mimicking a reduction of p35 in heterozygous knockout mice is associated with cognitive endophenotypes. Furthermore, a reduction of p35 in mice results in protein changes similar to schizophrenia post-mortem brain. Hence, heterozygous p35 knockout mice model both cognitive endophenotypes and molecular changes reminiscent of schizophrenia. These changes correlate with reduced acetylation of the histone deacetylase 1 target site H3K18 in mice. This site has previously been shown to be affected by truncated p35. By restoring H3K18 acetylation with the clinically used specific histone deacetylase 1 inhibitor MS-275 both cognitive and molecular endophenotypes of schizophrenia can be rescued in p35 heterozygous knockout mice. In summary, we suggest that reduced p35 expression in schizophrenia has an impact on synaptic protein expression and cognition and that these deficits can be rescued, at least in part, by the inhibition of histone deacetylase 1.

Dynamic changes to the epigenome play a critical role in establishing and maintaining cellular phenotype during differentiation, but little is known about the normal methylomic differences that occur between functionally distinct areas of the brain. We characterized intra- and inter-individual methylomic variation across whole blood and multiple regions of the brain from multiple donors.

Results

Distinct tissue-specific patterns of DNA methylation were identified, with a highly significant over-representation of tissue-specific differentially methylated regions (TS-DMRs) observed at intragenic CpG islands and low CG density promoters. A large proportion of TS-DMRs were located near genes that are differentially expressed across brain regions. TS-DMRs were significantly enriched near genes involved in functional pathways related to neurodevelopment and neuronal differentiation, including BDNF, BMP4, CACNA1A, CACA1AF, EOMES, NGFR, NUMBL, PCDH9, SLIT1, SLITRK1 and SHANK3. Although between-tissue variation in DNA methylation was found to greatly exceed between-individual differences within any one tissue, we found that some inter-individual variation was reflected across brain and blood, indicating that peripheral tissues may have some utility in epidemiological studies of complex neurobiological phenotypes.

Conclusions

This study reinforces the importance of DNA methylation in regulating cellular phenotype across tissues, and highlights genomic patterns of epigenetic variation across functionally distinct regions of the brain, providing a resource for the epigenetics and neuroscience research communities.

Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype–phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.

Author Summary

Epigenetic patterns vary during healthy ageing and development. Age-related DNA methylation changes have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To understand the biological mechanisms involved in potential longevity and rate of healthy ageing, we performed genome-wide association of epigenetic and genetic variation with both chronological age and age-related phenotypes. We identified hundreds of DNA methylation variants significantly associated with age and replicated these in an independent sample of young adult twins. Only a small proportion of these variants were also associated with age-related phenotypes. Therefore, the majority of age-related epigenetic changes do not contribute to rate of healthy ageing at later stages in life. Our results suggest that age-related changes in methylation occur throughout an individual's lifespan and that a proportion of these may be initiated from an early age. Intriguingly, a fraction of the age differentially methylated regions also associated with genetic variants in our sample, suggesting that DNA methylation may be a candidate mechanism of mediating not only environmental but also genetic effects on age-related phenotypes.

Studies of the major psychoses, schizophrenia (SZ) and bipolar disorder (BD), have traditionally focused on genetic and environmental risk factors, although more recent work has highlighted an additional role for epigenetic processes in mediating susceptibility. Since monozygotic (MZ) twins share a common DNA sequence, their study represents an ideal design for investigating the contribution of epigenetic factors to disease etiology. We performed a genome-wide analysis of DNA methylation on peripheral blood DNA samples obtained from a unique sample of MZ twin pairs discordant for major psychosis. Numerous loci demonstrated disease-associated DNA methylation differences between twins discordant for SZ and BD individually, and together as a combined major psychosis group. Pathway analysis of our top loci highlighted a significant enrichment of epigenetic changes in biological networks and pathways directly relevant to psychiatric disorder and neurodevelopment. The top psychosis-associated, differentially methylated region, significantly hypomethylated in affected twins, was located in the promoter of ST6GALNAC1 overlapping a previously reported rare genomic duplication observed in SZ. The mean DNA methylation difference at this locus was 6%, but there was considerable heterogeneity between families, with some twin pairs showing a 20% difference in methylation. We subsequently assessed this region in an independent sample of postmortem brain tissue from affected individuals and controls, finding marked hypomethylation (>25%) in a subset of psychosis patients. Overall, our data provide further evidence to support a role for DNA methylation differences in mediating phenotypic differences between MZ twins and in the etiology of both SZ and BD.

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10−4, permutation p = 1.0×10−3). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10−7). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.